Bastian Rieck

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 93

Top Venues

University of Heidelberg, Germany (PHD)

Education History

University of Heidelberg, Germany

PHD

Publications

Ernst Röell, Bastian Rieck
Differentiable Euler Characteristic Transforms for Shape Classification. ICLR (2024)
Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR (2024)
Corinna Coupette, Jilles Vreeken, Bastian Rieck
All the world's a (hyper)graph: A data drama. Digit. Scholarsh. Humanit. 39 (1) (2024)
Kelly Maggs, Celia Hacker, Bastian Rieck
Simplicial Representation Learning with Neural k-Forms. ICLR (2024)
Benjamin Holmgren, Eli Quist, Jordan Schupbach, Brittany Terese Fasy, Bastian Rieck
The Manifold Density Function: An Intrinsic Method for the Validation of Manifold Learning. CoRR (2024)
Jeremy Wayland, Corinna Coupette, Bastian Rieck
Mapping the Multiverse of Latent Representations. CoRR (2024)
Julius von Rohrscheidt, Bastian Rieck
Topological Singularity Detection at Multiple Scales. ICML (2023)
Bastian Rieck, Corinna Coupette
Evaluating the "Learning on Graphs" Conference Experience. CoRR (2023)
Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar
Metric Space Magnitude and Generalisation in Neural Networks. CoRR (2023)
Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
Curvature Filtrations for Graph Generative Model Evaluation. CoRR (2023)
Dominik Jens Elias Waibel, Ernst Röell, Bastian Rieck, Raja Giryes, Carsten Marr
A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images. ISBI (2023)
Kelly Maggs, Celia Hacker, Bastian Rieck
Simplicial Representation Learning with Neural k-forms. CoRR (2023)
Kalyan Varma Nadimpalli, Amit Chattopadhyay, Bastian Rieck
Euler Characteristic Transform Based Topological Loss for Reconstructing 3D Images from Single 2D Slices. CVPR Workshops (2023)
Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML (2023)
Joshua Southern, Jeremy Wayland, Michael Bronstein, Bastian Rieck
Curvature Filtrations for Graph Generative Model Evaluation. NeurIPS (2023)
Bastian Rieck
On the Expressivity of Persistent Homology in Graph Learning. CoRR (2023)
Ernst Röell, Bastian Rieck
Differentiable Euler Characteristic Transforms for Shape Classification. CoRR (2023)
Leon Hetzel, Johanna Sommer, Bastian Rieck, Fabian J. Theis, Stephan Günnemann
MAGNet: Motif-Agnostic Generation of Molecules from Shapes. CoRR (2023)
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
Preface. TAG-ML (2023)
Salome Kazeminia, Ario Sadafi, Asya Makhro, Anna Bogdanova, Carsten Marr, Bastian Rieck
Topologically-Regularized Multiple Instance Learning for Red Blood Cell Disease Classification. CoRR (2023)
Barbara Giunti, Janis Lazovskis, Bastian Rieck
DONUT - Creation, Development, and Opportunities of a Database. CoRR (2023)
Katharina Limbeck, Rayna Andreeva, Rik Sarkar, Bastian Rieck
Metric Space Magnitude for Evaluating Unsupervised Representation Learning. CoRR (2023)
Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar
Metric Space Magnitude and Generalisation in Neural Networks. TAG-ML (2023)
Hamed Alhoori, Edward A. Fox, Ingo Frommholz, Haiming Liu, Corinna Coupette, Bastian Rieck, Tirthankar Ghosal, Jian Wu
Who can Submit an Excellent Review for this Manuscript in the Next 30 Days? - Peer Reviewing in the Age of Overload. JCDL (2023)
Corinna Coupette, Sebastian Dalleiger, Bastian Rieck
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework. ICLR (2023)
Kalyan Varma Nadimpalli, Amit Chattopadhyay, Bastian Rieck
Euler Characteristic Transform Based Topological Loss for Reconstructing 3D Images from Single 2D Slices. CoRR (2023)
Franz Srambical, Bastian Rieck
Filtration Surfaces for Dynamic Graph Classification. CoRR (2023)
Daisuke Yoneoka, Bastian Rieck
A Note on Cherry-Picking in Meta-Analyses. Entropy 25 (4) (2023)
Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
Time-Inhomogeneous Diffusion Geometry and Topology. SIAM J. Math. Data Sci. 5 (2) (2023)
Julius von Rohrscheidt, Bastian Rieck
TOAST: Topological Algorithm for Singularity Tracking. CoRR (2022)
Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
Topological Graph Neural Networks. ICLR (2022)
Corinna Coupette, Jilles Vreeken, Bastian Rieck
All the World's a (Hyper)Graph: A Data Drama. CoRR (2022)
Dominik Jens Elias Waibel, Ernst Röell, Bastian Rieck, Raja Giryes, Carsten Marr
A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images. CoRR (2022)
Celia Hacker, Bastian Rieck
On the Surprising Behaviour of node2vec. CoRR (2022)
Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
Time-inhomogeneous diffusion geometry and topology. CoRR (2022)
Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. NeurIPS (2022)
Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA (2022)
Dominik Jens Elias Waibel, Scott Atwell, Matthias Meier, Carsten Marr, Bastian Rieck
Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction. CoRR (2022)
Dominik Jens Elias Waibel, Scott Atwell, Matthias Meier, Carsten Marr, Bastian Rieck
Capturing Shape Information with Multi-scale Topological Loss Terms for 3D Reconstruction. MICCAI (4) (2022)
Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
Taxonomy of Benchmarks in Graph Representation Learning. CoRR (2022)
Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. ICLR (2022)
Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. CoRR (2022)
Corinna Coupette, Sebastian Dalleiger, Bastian Rieck
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework. CoRR (2022)
Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov
The First Learning on Graphs Conference: Preface. LoG (2022)
Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
Taxonomy of Benchmarks in Graph Representation Learning. LoG (2022)
Florian Graf, Sebastian Zeng, Bastian Rieck, Marc Niethammer, Roland Kwitt
On Measuring Excess Capacity in Neural Networks. NeurIPS (2022)
Celia Hacker, Bastian Rieck
On the Surprising Behaviour of \textttnode2vec. TAG-ML (2022)
Leslie O'Bray, Bastian Rieck, Karsten M. Borgwardt
Filtration Curves for Graph Representation. KDD (2021)
Felix Hensel, Michael Moor, Bastian Rieck
A Survey of Topological Machine Learning Methods. Frontiers Artif. Intell. 4 (2021)
Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt
Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. CoRR (2021)
Michael F. Adamer, Leslie O'Bray, Edward De Brouwer, Bastian Rieck, Karsten M. Borgwardt
The magnitude vector of images. CoRR (2021)
Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew Hirn, Guy Wolf, Ladislav Rampásek
Towards a Taxonomy of Graph Learning Datasets. CoRR (2021)
Anja C. Gumpinger, Bastian Rieck, Dominik G. Grimm, Karsten M. Borgwardt
Network-guided search for genetic heterogeneity between gene pairs. Bioinform. 37 (1) (2021)
Malte Lücken, Daniel Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann Chen, Louise Deconinck, Angela Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Kim, Dominik Klein, Bony de Kumar, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Joaquin Melgarejo, Honey Mekonen, Maurizio Morri, Michaela Müller, Norma Neff, Sheryl Paul, Bastian Rieck, Kaylie Schneider, Scott Steelman, Michael Sterr, Daniel Treacy, Alexander Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela Pisco, Smita Krishnaswamy, Fabian J. Theis, Jonathan M. Bloom
A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. NeurIPS Datasets and Benchmarks (2021)
Bastian Rieck
Basic Analysis of Bin-Packing Heuristics. CoRR (2021)
Sarah C. Brüningk, Felix Hensel, Louis P. Lukas, Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck
Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classification. MLHC (2021)
Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
Topological Graph Neural Networks. CoRR (2021)
Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. CoRR (2021)
Robin Vandaele, Bastian Rieck, Yvan Saeys, Tijl De Bie
Stable topological signatures for metric trees through graph approximations. Pattern Recognit. Lett. 147 (2021)
Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck, Sarah C. Brüningk
Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification. CoRR (2021)
Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
Weisfeiler and Leman go Machine Learning: The Story so far. CoRR (2021)
Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck
Graph Kernels: State-of-the-Art and Future Challenges. CoRR (2020)
Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Topological Autoencoders. ICML (2020)
Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. NeurIPS (2020)
Jannis Born, Nina Wiedemann, Gabriel Brändle, Charlotte Buhre, Bastian Rieck, Karsten M. Borgwardt
Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis. CoRR (2020)
Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. CoRR (2020)
Stefan Groha, Caroline Weis, Alexander Gusev, Bastian Rieck
Topological Data Analysis of copy number alterations in cancer. CoRR (2020)
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt
Set Functions for Time Series. ICML (2020)
Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck
Path Imputation Strategies for Signature Models. CoRR (2020)
Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck
Graph Kernels: State-of-the-Art and Future Challenges. Found. Trends Mach. Learn. 13 (5-6) (2020)
Caroline Weis, Max Horn, Bastian Rieck, Aline Cuénod, Adrian Egli, Karsten M. Borgwardt
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra. Bioinform. 36 (Supplement-1) (2020)
Christoph D. Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt
Graph Filtration Learning. ICML (2020)
Sarah C. Brüningk, Felix Hensel, Catherine R. Jutzeler, Bastian Rieck
Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design. CoRR (2020)
Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz
Machine learning for early prediction of circulatory failure in the intensive care unit. CoRR (2019)
Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten M. Borgwardt
Wasserstein Weisfeiler-Lehman Graph Kernels. CoRR (2019)
Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Topological Autoencoders. CoRR (2019)
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt
Set Functions for Time Series. CoRR (2019)
Bastian Rieck, Filip Sadlo, Heike Leitte
Topological Machine Learning with Persistence Indicator Functions. CoRR (2019)
Bastian Rieck, Markus Banagl, Filip Sadlo, Heike Leitte
Persistent Intersection Homology for the Analysis of Discrete Data. CoRR (2019)
Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten M. Borgwardt
Wasserstein Weisfeiler-Lehman Graph Kernels. NeurIPS (2019)
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. MLHC (2019)
Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. ICLR (Poster) (2019)
Bastian Rieck, Christian Bock, Karsten M. Borgwardt
A Persistent Weisfeiler-Lehman Procedure for Graph Classification. ICML (2019)
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. CoRR (2019)
Boyan Zheng, Bastian Rieck, Heike Leitte, Filip Sadlo
Visualization of Equivalence in 2D Bivariate Fields. Comput. Graph. Forum 38 (3) (2019)
Christian Bock, Matteo Togninalli, M. Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, Karsten M. Borgwardt
A Wasserstein Subsequence Kernel for Time Series. ICDM (2019)
Kai Sdeo, Bastian Rieck, Filip Sadlo
Visualization of Fullerene Fragmentation. PacificVis (2018)
Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. CoRR (2018)
Lutz Hofmann, Bastian Rieck, Filip Sadlo
Visualization of 4D Vector Field Topology. Comput. Graph. Forum 37 (3) (2018)
Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
Association mapping in biomedical time series via statistically significant shapelet mining. Bioinform. 34 (13) (2018)
Karsten Hanser, Ole Klein, Bastian Rieck, Bettina Wiebe, Tobias Selz, Marian Piatkowski, Antoni Sagristà, Boyan Zheng, Mária Lukácová-Medvid'ová, George Craig, Heike Leitte, Filip Sadlo
Visualization of Parameter Sensitivity of 2D Time-Dependent Flow. ISVC (2018)
Bastian Rieck, Ulderico Fugacci, Jonas Lukasczyk, Heike Leitte
Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks. IEEE Trans. Vis. Comput. Graph. 24 (1) (2018)
Bastian Rieck, Heike Leitte
Exploring and Comparing Clusterings of Multivariate Data Sets Using Persistent Homology. Comput. Graph. Forum 35 (3) (2016)
Bastian Rieck, Heike Leitte
Persistent Homology for the Evaluation of Dimensionality Reduction Schemes. Comput. Graph. Forum 34 (3) (2015)
Bastian Rieck, Heike Leitte
Structural Analysis of Multivariate Point Clouds Using Simplicial Chains. Comput. Graph. Forum 33 (8) (2014)
Bastian Rieck, Hubert Mara, Heike Leitte
Multivariate Data Analysis Using Persistence-Based Filtering and Topological Signatures. IEEE Trans. Vis. Comput. Graph. 18 (12) (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Bastian Rieck